Hello List,
I'm trying to do a paired t-test, and I'm wondering if it's consistent
with equations. I have a dataset that has a response and two
treatments (here's an example):
ID trt order resp
17 1 0 1 0.0037513592
18 2 0 1 0.0118723051
19 4 0 1 0.0002610251
20 5 0 1 -0.0077951450
21 6 0 1 0.0022339952
22 7 0 2 0.0235195453
The subjects were randomized and assigned to receive either the
treatment or the placebo first, then the other. I know I'll
eventually have to move on to a GLM or something that incorporates the
order, but for now I wanted to start with a simple t.test. My problem
is that, if I get the responses into two vectors x and y (sorted by
ID) and do a t.test, and then compare that to a formula t.test, they
aren't the same.
> t.test(x,y,paired=TRUE)
Paired t-test
data: x and y
t = -0.3492, df = 15, p-value = 0.7318
alternative hypothesis: true difference in means is not equal to 0
95 percent confidence interval:
-0.010446921 0.007505966
sample estimates:
mean of the differences
-0.001470477
> t.test(resp~trt,data=dat1[[3]],paired=TRUE)
Paired t-test
data: resp by trt
t = -0.3182, df = 15, p-value = 0.7547
alternative hypothesis: true difference in means is not equal to 0
95 percent confidence interval:
-0.007096678 0.005253173
sample estimates:
mean of the differences
-0.0009217521
What I'm assuming is that the equation isn't retaining the inherent
order of the dataset, so the pairing isn't matching up (even though
the dataset is ordered by ID). Is there a way to make the t.test
retain the correct ordering?
Thanks,
Sam
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